Spectroscopic imaging combines digital imaging and optical spectroscopy techniques, which can include Raman scattering, fluorescence, photoluminescence, laser induced breakdown, ultraviolet, visible and infrared absorption spectroscopies. When applied to the chemical analysis of materials, spectroscopic imaging is also referred to as hyperspectral imaging or chemical imaging. Instruments for performing spectroscopic (i.e. chemical) imaging typically comprise an illumination source, image gathering optics, focal plane array (FPA) imaging detectors and imaging spectrometers.
In general, the size or accessibility of a sample determines the choice of image gathering optic. For example, a microscope is typically employed for the analysis of sub-micron to millimeter spatial dimension samples. For larger objects, in the range of millimeter to meter dimensions, macro lens optics are appropriate. For samples located within relatively inaccessible environments, flexible fiberscope or rigid borescopes can be employed. For very large scale objects, such as planetary objects, or for objects located at a significant stand-off distance from a sensor, telescopes are appropriate image gathering optics.
Two-dimensional, imaging FPA detectors are typically employed to detect images formed by the various optical systems. The choice of FPA detector is governed by the spectroscopic technique employed to characterize the sample of interest. For example, silicon (Si) charge-coupled device (CCD) detectors or complementary metal-oxide-semiconductor (CMOS) detectors are typically employed with visible wavelength fluorescence and Raman spectroscopic imaging systems, while indium gallium arsenide (InGaAs) FPA detectors are typically employed with near infrared spectroscopic imaging systems.
Conventional spectroscopic devices operate over a limited range of wavelengths due to the operation ranges of the detectors or imaging spectrometers possible. This enables analysis in the ultraviolet (UV), visible (VIS), near infrared (NIR), short wave infrared (SWIR), mid infrared (MIR), and long wave infrared (LWIR) wavelengths, as well as some overlapping ranges. These correspond to wavelengths of about 180-380 nm (UV), about 380-700 nm (VIS), about 700-2500 nm (NIR), about 850-1700 nm (SWIR), about 700-1700 (VIS-NIR), about 2500-5000 nm (MIR), and about 5000-25000 (LWIR).
Spectroscopic imaging of a sample is commonly implemented by one of two methods. First, point-source illumination can be used on a sample to measure the spectra at each point of the illuminated area. Second, spectra can be collected over the entire area encompassing a sample simultaneously using an electronically tunable optical imaging filter such as an acousto-optic tunable filter (AOTF), a liquid crystal tunable filter (LCTF), or a multi-conjugate tunable filter (MCF, which is a type of LCTF). Here, the organic material in such optical filters is actively aligned by applied voltages to produce the desired bandpass and transmission function. In hyperspectral imaging (HSI), the spectra obtained for each pixel of an image forms a complex data set referred to as a hyperspectral image. Hyperspectral images may contain the intensity values at numerous wavelengths or the wavelength dependence of each pixel element in the image. Multivariate routines, such as chemometric techniques, may be used to convert spectra to classifications.
A LCTF uses birefringent retarders to distribute the light energy of an input light signal over a range of polarization states. The polarization state of light emerging at the output of the LCTF is caused to vary as a function of wavelength due to differential retardation of orthogonal components of the light, contributed by the birefringent retarders. The LCTF discriminates for wavelength-specific polarization using a polarizing filter at the output. The polarizing filter passes the light components in the output that are rotationally aligned to the polarizing filter. The LCTF is tuned by adjusting the birefringence of the retarders so that a specific discrimination wavelength emerges in a plane polarized state, aligned to the output polarizing filter. Other wavelengths that emerge in other polarization states and/or alignments are attenuated.
A highly discriminating spectral filter is possible using a sequence of several birefringent retarders. The thicknesses, birefringences, and relative rotation angles of the retarders are chosen to correspond to the discrimination wavelength. More specifically, the input light signal to the filter becomes separated into orthogonal vector components, parallel to the respective ordinary and extraordinary axes of each birefringent retarder when encountered along the light transmission path through the filter. These separated vector components are differentially retarded due to the birefringence; such differential retardation also amounts to a change in their polarization state. For a plane polarized component at the input to the filter, having a specific rotational alignment at the input to the filter and at specific discrimination wavelengths, the light components that have been divided and subdivided all emerge from the filter in the same polarization state and alignment, namely plane polarized and in alignment with the selection polarizer (i.e., the polarizing filter) at the output.
A filter as described is sometimes termed a birefringent interference filter because the components that have been divided and subdivided from the input and interfere positively at the output selection polarizer are the components that are passed. Such filters also are sometimes described with respect to a rotational twist in the plane polarization alignment of the discriminated component between the input and the selection polarizer at the output.
There are several known configurations of spectral filters comprising birefringent retarders, such as the Lyot, Solc and Evans types. Such filters can be constructed with fixed (non-tunable) birefringent crystals for the retarders. A filter with retarders that are tuned in unison permits adjustment of the bandpass wavelength. Tunable retarders can comprise liquid crystals or composite retarder elements each comprising a fixed crystal and an optically aligned liquid crystal.
The thicknesses, birefringences, and rotation angles of the retarders are coordinated such that each retarder contributes part of the necessary change in polarization state to alter the polarization state of the passband wavelength from an input reference angle to an output reference angle. The input reference angle may be, for example, 45° to the ordinary and extraordinary axes of a first retarder in the filter. The output reference angle is the rotational alignment of the polarizing filter (or selection polarizer).
A spectral filter may have a comb-shaped transmission characteristic. Increasing or decreasing the birefringence when tuning to select the discrimination wavelength (or passband), stretches or compresses the comb shape of the transmission characteristic along the wavelength coordinate axis.
If the input light is randomly polarized, the portion that is spectrally filtered is limited to the vector components of the input wavelengths that are parallel to one of the two orthogonal polarization components that are present. Only light at the specific wavelength, and at a given reference polarization alignment at the input, can emerge with a polarization angle aligned to the rotational alignment of the selection polarizer at the output. The light energy that is orthogonal to the reference alignment at the input, including light at the passband wavelength, is substantially blocked.
A LCTF thus passes only one of two orthogonal components of input light. The transmission ratio in the passband is at a maximum for incident light at the input to the LCTF that is aligned to a reference angle of the LCTF. Transmission is at minimum for incident light energy at the input is orthogonal to that reference angle. If the input light in the passband is randomly polarized, the best possible transmission ratio in the passband is fifty percent. It is therefore desirable to devise a system and method wherein both orthogonal components of the input light are allowed to transmit through the tunable filter, thereby effectively doubling the throughput at the filter output.
Even using a dual polarization approach, each LCTF is limited to single bandpass, low throughput operation. Therefore, multiple, discrete bandpass measurements are required for analyte discrimination. The need for multiple measurements increases the overall measurement time.
Multivariate Optical Computing (MOC) is an approach which utilizes a compressive sensing device (e.g. an optical computer) to analyze spectroscopic data as it is collected. Other approaches utilize hard coated optical computing filters such as Multivariate Optical Elements (MOEs). MOEs are application-specific optical thin film filters that are used in transmission and reflectance modes. Thin film filters are interference filters with very thin structured layers of different materials with thicknesses on the order of the wavelengths of visible light (for example, 500 nm). Layers at this scale can have remarkable reflective properties due to the light wave interference and the difference in refractive index between the layers, the air, and the substrate. These effects alter the way the optic reflects and transmits light, an effect known as thin film interference. In manufacturing, thin film layers can be achieved through the deposition of one or more thin layers of material onto a substrate. This can be done using a physical vapor deposition process, such as evaporation or sputter deposition, or a chemical process such as chemical vapor deposition. The radiometric response of a MOE-based instrument is proportional to the intended analyte in an associated matrix.
Compressive sensing is the process in which a fully resolved waveform or image is reconstructed from a small set of sparse measurements. A sparse sample implies a waveform or image data set with coefficients close to or equal to zero. Compressive sensing utilizes the redundancy in information across the sampled signal similar to lossy compression algorithms utilized for digital data storage. A fully expanded data set may be created through the solution of an undetermined linear system, an equation where the compressive measurements collected are smaller than the size of the original waveform or image. Compressive measurements can ultimately lead to expedited HSI data collections while still preserving most of the original spectroscopic and spatial information.
While compressive sensing holds potential for decreasing measurement time, the use of MOEs have limitations. For example, MOEs are fixed and lack flexibility for adapting to different analytes. There exists a need for an adaptable filter that can be used to detect a wide variety of analytes while reducing overall measurement time. It would be beneficial if a plurality of such filters could be arranged in a dual polarization configuration to further increase speed of analysis and also provide for assessing multiple analytes simultaneously.